Research Interests

How robust are functional networks to genetic perturbations? On short timescales, like a cell cycle, cells need be
robust to perturbations (elastic), however on long evolutionary timescales mutations may allow cells
to respond to adapt to their environment (plastic). So how hard is it to generate a new functional module that
subsequently is robust to genetic perturbations on short time scales? Does redundancy in network functions allow cells to be more
robust to perturbations? And what are the underlying molecular mechanisms that are responsible for the network changes?

We address these questions by removing genes nearly essential to polarization in budding yeast and subsequently evolving these “nearly dead”
cells to higher fitness (see cartoon above). Surprisingly, the evolved cells rapidly increased their fitness. Using light microscopy, growth rate/doubling time
measurements and genetic analysis, we study how these cells rescue polarization. These measurements together with, minimal in vitro
systems and modelling should shed light on questions like: Did they fix the perturbation, did they strengthen other polarization mechanisms or did they evolve a new one?

We also use this system to ask other questions about evolution, like, how predictable is an evolutionary trajectory and how much does
this depend on the specifics of the selection. So, is adapting to genetic perturbations, like cancer cells do, intrinsically more predictable than adaptations to a new environment?
Or can you ever go back in evolution or is evolution always irreversible? So what happens if I first delete a gene, adapt cells to higher fitness
and subsequently reintroduce the gene and evolve the cells again? Are there regimes where the cells will evolve back to the original state?

To decipher the underlying molecular mechanisms of adaptation we use quantitative fluorescence life cell microscopy in combination with modelling, as well as minimal
biophysical in vitro systems. With these in vitro systems we want to (1) achieve a mechanistic understanding of the role of different key components for polarization,
(2) characterize if, and if so how, the interactions of those components lead to the formation of a single site of activated Cdc42 on an artificial liposome membrane, (3)
combine our mechanistic insights from in vitro experiments with modelling to describe the in vivo polarity network and its adaptive potential.